able to provide more accurate forecasting results than linear models. Therefore, simple autoregressive processes are … observations and autoregression residuals. The proposed forecasting models are applied to a large set of macroeconomic and … autoregression residuals, are somewhat able to provide better forecasting results than simple linear models. Thus, it may be …

(asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We … variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk …

forecasting horizon we either favour a denoising step plus an ARIMA forecast or an multiscale wavelet decomposition plus an ARIMA … incorporating the wavelet transform in existing forecasting methods can improve their quality. The article aims to verify this by … characteristics. We find that wavelets do improve the forecasting quality. Depending on the data's characteristics and on the …

. Preliminary evidence that mixed frequency based forecasting models yield improvements over standard fixed frequency models is …